Analyte detection and methods therefor

ABSTRACT

Disclosed are methods and systems for analyte detection in a sample and more particularly, a biological sample. Methods and systems particularly relate to differentiating and/or identifying cell types in biological samples, such as blood samples, by adding antibodies specific to predetermined CD antigens. Other methods and systems relate to controlling the dynamic range of an assay for analyte detection.

TECHNICAL FIELD

This technology relates to analyte detection. More particularly, thistechnology relates to methods and systems for identifying cell types insamples. This technology also relates to methods and systems forcontrolling dynamic range of assay quantification for analyte detection.

RELATED APPLICATION

This application claims the benefit of U.S. Provisional Application No.62/153,523, entitled “Method and System for Identifying Cells in BloodSamples by Adding Antibodies Specific to Clusters of Differentiation”,filed on 28 Apr. 2015, the subject matter of which is incorporatedherein by reference in its entirety.

This application claims the benefit of U.S. Provisional Application No.62/155,486, entitled “Method and System for Controlling Dynamic Range ofAssay Quantification for Analyte Detection”, filed on 1 May 2015, thesubject matter of which is incorporated herein by reference in itsentirety.

BACKGROUND

Analyte detection remains an important tool not only for medicalapplications but also broadly for agricultural and veterinaryapplications. Blood cell count is an important diagnostic tool, whichprovides valuable information regarding a patient's health. The completeblood count determines the number of various types of blood cells perunit volume of patient's blood. One type of blood cell that is countedis the white blood cell (WBC). High levels of white blood cells incirculation are indicative of a development of a bacterial infectionand/or inflammation, and information regarding differentiation of whiteblood cells in a blood sample can provide one with a detailedinformation with respect to certain specific conditions, such asallergic reactions, leukaemia, human immunodeficiency virus (HIV), andthe general state of the immune system. The elevated number of red bloodcells can indicate development of a number of conditions, such asanaemia and bone marrow disorders. Change in platelet number incirculation can flag up the risk of bleeding or clots in a patient, andit can also indicate a development of a viral infection.

Clusters of differentiation (CD) antigens are membrane proteinsexpressed on the surface of blood cells that are widely used for anidentification of different types of white blood cell, as well aserythrocytes and platelets. The nomenclature of the clusters ofdifferentiation has been proposed and established at the FirstInternational Workshop and Conference on Human Leukocyte DifferentiationAntigens (HLDA). Immunologists globally generated large numbers ofmonoclonal antibodies reacting with leukocyte cell surface molecules,and each of these antibodies was associated with differentnomenclatures. In the absence of comparative studies, it was oftenimpossible to tell whether the same molecule was recognised by more thanone antibody. The approach of the workshops was to code and classifyantibodies and to send them to multiple participating laboratories toperform a blind analysis allowing one to compare multiple cell types.The data obtained were collated and analysed by a statistical procedureof “cluster analysis.” This analytical method identified clusters ofantibodies with very similar patterns of binding to leukocytes atvarious stages of differentiation: as such, the “cluster ofdifferentiation” (CD) nomenclature was created. The cluster ofdifferentiation nomenclature allowed the scientific community tocommunicate results in a universal language.

The cluster of differentiation nomenclature defines different monoclonalantibodies from different sources that recognize identical antigens. Aproposed surface molecule is assigned a CD number, once two specificmonoclonal antibodies are shown to bind to the molecule. Two commonlyused CD molecules are CD4 and CD8, which are, in general, used asmarkers for two different subtypes of T-lymphocytes, T-helpers andcytotoxic T cells, respectively. CD4 is specifically recognized andbound by HIV, which leads to a viral infection and destruction of CD4+ Tcells. At the same time, in many cases, elevated proportions of CD8+cells are observed in persons infected with HIV. Thus, the conventionalapproaches to diagnosing HIV infection have included monitoring CD4+count, the percentage of CD4+ and CD4+/CD8+ ratio.

Development of methods of cell counting and differentiation started morethan a century ago. One of the oldest methods for blood cell countingemploys haemocytometers. These are manual cell counting devicesconsisting of a thick glass microscope slide with a rectangularindentation that creates a chamber. This chamber is engraved with alaser-etched grid of perpendicular lines. The device is carefullycrafted so that the area bounded by the lines is known, and the depth ofthe chamber is also known. It is, therefore, possible to count thenumber of cells or particles in a specific volume of fluid, e.g., blood,and thereby calculate the concentration of cells in the fluid overall.

Another method of cell counting is called flow cytometry. It is a modernlaser-based, biophysical technology employed not only in cell counting,but also in cell sorting, biomarker detection and protein engineering,by suspending cells in a stream of fluid and passing them through anelectronic detection apparatus. It allows simultaneous multi-parametricanalysis of the physical and chemical characteristics of up to thousandsof particles per second.

Flow cytometry is routinely used in the diagnosis of health disorders,especially blood cancers, but has many other applications in basicresearch, clinical practice, and clinical trials. A common variation isto physically sort particles based on their properties so as to purifypopulations of interest.

There are also known numerous methods of pathogen detection andidentification. One of the oldest methods is Gram staining. Gramstaining, also called Gram's method, is a method of differentiatingbacterial species into two large groups (Gram-positive andGram-negative). Gram staining differentiates bacteria by the chemicaland physical properties of their cell walls by detecting peptidoglycan,which is present in a thick layer in gram-positive bacteria. In a Gramstain test, Gram-positive bacteria retain the crystal violet dye, whilea counter-stain (commonly safranin or fuchsine) added after the crystalviolet gives all Gram-negative bacteria a red or pink colouring. TheGram stain is almost always the first step in the identification of abacterial organism. While Gram staining is a valuable diagnostic tool inboth clinical and research settings, not all bacteria can bedefinitively classified by this technique.

The polymerase chain reaction (PCR) is another technology in moleculebiology used to amplify a specific region of a deoxyribonucleic acid(DNA) strand across several orders of magnitude, generating thousands tomillions of copies of a particular DNA sequence. PCR permits earlydiagnosis of malignant diseases, such as leukaemia and lymphomas, whichis currently the highest-developed in cancer research and is alreadybeing used routinely. Culturing of organisms has been also used inclinical diagnostic testing for bacterial enteric pathogens. Inculturing, samples are often incubated in media selective for a pathogenbeing investigated, normally containing inhibitors to non-targetspecies. The growth of the pathogen can thereafter be determinedoptically. These culture methods include the Microscopic ObservationDrug Susceptibility assay (MODS). It is a culture method shown to bemore sensitive, faster and cheaper test than current culture-based testsfor tuberculosis. The Microscopic Observation Drug Susceptibility assayinvolves direct observation of Mycobacterium tuberculosis andsimultaneously yields drug-resistance.

Immunomagnetic separation (IMS) is another method that can efficientlyisolate cells out of body fluid or cultured cells. It can also be usedas a method of quantifying the pathogenicity of food, blood or faeces.DNA analysis have supported the combined use of both this technique andPCR. Immunomagnetic separation methods are based on the attachment ofsmall magnetisable particles to cells via antibodies or lectins. Whenthe mixed population of cells is placed in a magnetic field, those cellsthat have beads attached will be attracted to the magnet and may thus beseparated from the unlabelled cells. Several makes of bead areavailable, some of which are designed specifically for cell sorting, andothers that are designed for purifying molecules (particularly nucleicacids) but that may be adapted for cell sorting if necessary. Thedifferent types of beads work on the same principle, but the strength ofthe magnetic field required to separate the cells differs depending onthe size of the beads.

Antibody-coated paramagnetic beads will bind to antigens present on thesurface of cells, thus capturing the cells and facilitate theconcentration of these bead-attached cells. The concentration process iscreated by a magnet placed on the side of the test tube bringing thebeads to it. Antibody-coated magnetic beads can be used to targetantigens specific to the target pathogen, and to separate pathogens froma sample.

The enzyme-linked immunosorbent assay (ELISA) is yet another test thatuses antibodies and colour change to identify a substance. ELISA is apopular format of “wet-lab” type analytic biochemistry assay that uses asolid-phase enzyme immunoassay (EIA) to detect the presence of asubstance, usually an antigen, in a liquid sample or wet sample. TheELISA has been used as a diagnostic tool in medicine and plantpathology, as well as a quality-control check in various industries.Performing an ELISA involves at least one antibody with specificity fora particular antigen. A sample with an unknown amount of antigen isimmobilized on a solid support (usually a polystyrene microtiter plate)either non-specifically (via adsorption to the surface), or specifically(via capture by another antibody specific to the same antigen, in a“sandwich” ELISA). After the antigen is immobilized, the detectionantibody is added, forming a complex with the antigen. The detectionantibody can be covalently linked to an enzyme, or can itself bedetected by a secondary antibody that is linked to an enzyme throughbioconjugation.

Thus, there are a number of methods of distinguishing cell types inblood samples known in the art, however these methods do not alwaysprovide satisfactory results and require complex, slow, and bulkyequipment. Hence, there is still a need in the art to improve themethods for distinguishing cell types in blood samples.

Immunoassays are bioanalytical methods used for detecting the presenceor quantity of one or more target analytes in a biological sample basedon the principle of immunocomplexes formed by antigen-antibodyinteractions. These assays generally utilize antigen-antibody complexesto generate measurable signals, which indicate the quantity of one ormore analytes present in the sample. Immunoassays have been widely usedin disease diagnosis, drug discovery, and pharmaceutical analysis.

Different types of immunoassays are used for detection andquantification of analytes, each suited for a specific application.Enzyme immunoassay methods utilize enzyme labelled reagents forspecifically binding to a target analyte (antigen or antibody). Thebound reagent is quantified as a measure of enzyme activity that yieldsa coloured, fluorescent, luminescent, or otherwise modified product uponadding a suitable substrate such as a “development fluid.” Incompetitive immunoassays, enzyme conjugated analytes compete withanalytes present in the sample, for binding sites on capture antibodiescoated onto a support surface. The greater the concentration of analytein the sample results in lesser binding of conjugated analytes to theantibodies.

The dynamic range of an assay is the range of target analyteconcentration over which an accurate measurement can be made. Itimportant that the concentration of a target molecule in a sample iswithin the dynamic range of the assay. The dynamic range of the assaycan be influenced by factors such as detection limits of a readingdevice, a rate of development of the development fluid or othersubstrate, incubation time, and so forth. For example, if thefluorescence signal from reporters bound to a high concentration analyteis too high, then the optical sensor (e.g., photodiode) may be saturatedso it is not possible to get a precise reading of the actual lightlevel, and therefore not possible to determine the analyteconcentration. Similarly, if the rate of development of a developmentfluid is too fast then the development fluid may become completelydeveloped before a measurement is taken so that it is not possible todetermine exactly how fast the development fluid developed, andtherefore not possible to determine the exact analyte concentration. Inexisting multiplexed assay methods, various strategies were adopted toenhance the dynamic range of assay performance including the use ofserial dilution methods, flow cytometry bead-based platforms, andco-coupling of reagent and neutral reagent to a substrate under suitableconditions. Other methods have concentrated on increasing the dynamicrange of the instrumentation used to check the signal. For example,chemiluminescence based multiplex assays facilitate determining theconcentration of different target analytes by individually analysing thelight emitted from antibodies bound to each region comprising differenttargets. However, the above methods do not always provide accurate andfast analyte detection especially in the circumstances when multipleanalytes are present in a sample. Hence, there is still a need in theart for improving the methods for analyte detection.

It will be appreciated that reference herein to “preferred” or“preferably” is intended as exemplary only.

SUMMARY

In one broad form, the present technology generally relates to a methodand system for differentiating and/or identifying cell types inbiological samples, such as blood samples, by adding antibodies specificto predetermined CD antigens. In one embodiment, following an incubationof the antibodies allowing them to bind to the CD antigens, an initialantibody concentration can be calculated based on an amount ofantibodies introduced and a sample volume. Alternatively, the bloodsample could be assayed to determine an initial concentration of eachantibody. Subsequently, the blood sample is filtered to separate out thecells and bound antibodies. The filtrate, or a fraction thereof isthereafter assayed again to determine a final concentration of eachantibody that did not bind to surfaces of the cells. In this technology,the greater the number of cells expressing a particular CD antigen onthe cell surface, the lower the concentration of antibody that willremain in the filtrate. The number and/or types of the cells expressingeach CD antigen are then determined based on calculating a change inantibody concentration prior to filtration and after filtration.

In other embodiments, the number of antibodies bound to the cells areassayed directly whilst attached to the cells. In another embodiment,the number of antibodies bound the cells are assayed directly afterbeing acted upon to delink, uncouple or unbind them from the cells. Inthese embodiments, the greater the number of cells expressing aparticular CD antigen on the cell surface, the greater the concentrationof antibody determined by the assay.

In various embodiments, CD antigens can be replaced with any othersuitable cell surface proteins, or other molecules specific to cellsurface of a particular cell type or group of cell types. In yet moreembodiments, CD antigens may include or be substituted with any naturalor synthetic protein suitable for measuring antibody concentrations asdiscussed herein. Moreover, antibodies could be replaced with any othertype of chemical molecules with high affinity only for one particularprotein (e.g., aptamers), or other cell surface molecules.

According to one aspect of this disclosure, a method for differentiatingcells in a biological sample is provided. The method comprises the stepsof: (i) contacting the biological sample with marker-specific moleculesagainst at least one surface marker of the cells, where themarker-specific molecules are associated with a first count parameter;(ii) allowing the cells in the biological sample to bind to themarker-specific molecules to produce bound marker-specific molecules;(iii) filtering the biological sample by removing the cells and thebound marker-specific molecules from the biological sample to generate afiltrate; (iv) determining, by a sensor or an analyser, a second countparameter of the marker-specific molecules in the filtrate; and (v)calculating, by a computing device or the analyser, a number of thecells in the biological sample based on the difference between the firstcount parameter and the second count parameter.

In some embodiments, the first count parameter includes a firstconcentration of the marker-specific molecules, while the second countparameter includes a second concentration of the marker-specificmolecules. In other embodiments, the first and second count parametersmay relate to a count number.

In some embodiments, the marker-specific molecules include one or moreantibodies of at least one type and/or specificity. In otherembodiments, the marker-specific molecules include one or more aptamersof at least one type and/or specificity.

In some embodiments, each of the surface markers is associated with adistinct cluster of differentiation.

In some embodiments, the method may further include the step ofidentifying one or more types of the cells based on the differencebetween the first count parameter and the second count parameter. In yetmore embodiments, the method may further include the step of passing thefiltrate onto an analyser structure containing discrete regions, towhich the surface markers are bound. In some embodiments, the method mayfurther include the step of comprising incubating the filtrate in theanalyser structure.

In some embodiments, the at least one surface marker of the cellsincludes one or more pathogen surface markers that facilitateidentifying pathogens in the biological sample. In some embodiments, theat least one surface marker of the cells includes one or more mycoplasmasurface markers that facilitate detecting mycoplasma growth in celllines.

In some embodiments, the first count parameter of the marker-specificmolecules is predetermined. In other embodiments, the method may furtherinclude the step of determining, by the sensor or the analyser, thefirst count parameter of the marker-specific molecules prior togenerating the filtrate. In yet more embodiments, the method may furtherinclude the step of determining, by the computing device or theanalyser, a disease of an individual based on the difference between thefirst count parameter and the second count parameter.

In certain embodiments, the method may further include the steps ofmaintaining, by the computing device or the analyser, a plurality oftreatment recommendations; and providing, by the computing device or theanalyser, one of the treatment recommendations based on determination ofthe disease of the individual.

According to another aspect of this disclosure, a method fordifferentiating cells in a biological sample is provided. The methodcomprises the steps of: (i) contacting the biological sample withmarker-specific molecules against at least one surface marker of thecells, wherein the marker-specific molecules are associated with a countparameter; (ii) allowing the cells in the biological sample to bind tothe marker-specific molecules to produce bound marker-specificmolecules; (iii) treating or filtering the biological sample to removethe cells and the bound marker-specific molecules from the biologicalsample and generate a filtrate; (iv) determining, by a sensor or ananalyser, a count parameter of the bound marker-specific molecules; and(v) calculating, by the analyser, a number of the cells of one or moretypes based on the count parameter of the marker-specific molecules andthe count parameter of the bound marker-specific molecules.

According to yet another aspect of this disclosure, a system fordifferentiating cells in a biological sample is provided. The systemcomprises: (i) a sampling module configured to contact the biologicalsample with marker-specific molecules against at least one surfacemarker of the cells and allow the cells in the biological sample to bindto the marker-specific molecules to produce bound marker-specificmolecules, where the marker-specific molecules are associated with afirst count parameter; (ii) a filter configured to filter the biologicalsample by removing the cells and the bound marker-specific moleculesfrom the biological sample to generate a filtrate; and (iii) an analyserconfigured to determine a second count parameter of the marker-specificmolecules in the filtrate and calculate a number of the cells in thebiological sample based on the difference between the first countparameter and the second count parameter.

According to yet another aspect of this disclosure, a system fordifferentiating cells in a biological sample is provided. The systemcomprises: (i) a sampling module configured to contact the biologicalsample with marker-specific molecules against at least one surfacemarker of the cells and allow the cells in the biological sample to bindto the marker-specific molecules to produce bound marker-specificmolecules, where the marker-specific molecules are associated with afirst count parameter; (ii) a filter configured to filter the biologicalsample by removing the cells and the bound marker-specific moleculesfrom the biological sample; and (iii) an analyser configured todetermine a second count parameter of the marker-specific molecule boundto the cells (either whilst bound or once acted upon to unbind them fromthe cell) and calculate a number of the cells in the biological samplebased on the difference between the first count parameter and the secondcount parameter.

In some embodiments, the analyser includes a computing device having atleast one processor and a memory, which stores processor-executableinstructions that, when executed by the at least one processor, causethe at least one processor to determine the second concentration of theat least one marker-specific molecule in the filtrate, and calculate thenumber of the cells in the biological sample based on the differencebetween the first concentration and the second concentration.

In some embodiments, the system can be implemented as a portable and/ordisposable system to provide a fast, field/point-of-care-based methodapplicable for cell counting and differentiation for various purposesincluding, but not limited to diagnostics, health monitoring, bloodtyping and monitoring of HIV progression, distinguishing betweeninfections of viral or bacterial origin, pathogen detection andidentification, diagnostics based on biological fluid and tissuesamples, utilization in food industry, agricultural applications, waterquality testing, and/or detecting mycoplasma contamination in culturedcell lines. An advantage of this technology is that it can beimplemented more easily in a small form factor microfluidic system thantraditional cell counting techniques such as flow cytometry. Therefore,it enables cell counting in portable systems which has many beneficialapplications.

In general, the methods of this disclosure can be practiced for cellcounting in any solution or suspension used for commercial andnon-commercial applications, which may contain organic or inorganiccomponents. For example, the methods of this disclosure can be practicedfor any biological fluid derived from a human, animal, or related to anybiological organism, including plants, fungi, bacteria, orarchaebacteria. In some embodiments, the methods of this disclosure canbe practiced for blood cell counting.

According to yet more embodiments, the methods and systems of thisdisclosure can be practiced for determining if a patient has aparticular disease and/or if said patient requires a correspondingtreatment. This determination can be based on the results ofdifferentiating/identifying of cells in a biological sample as describedherein. For example, determination of white blood cell count using themethods of this disclosure could be used to determine if an individualhas an infection leading to treatment with antibiotics. In anotherembodiment, the determination of red blood cell count using the methodsof this disclosure can be used to determine if an individual is anaemicand needs to be treated, for example, with iron supplements. In yetanother embodiment, the determination of decreased white or red bloodcell count may be a consequence of treatment with certain drugs, forexample, clozapine. Therefore, the choice of treatment can also dependon a cell count. Determination of blood cell count and cell count inother biological samples can, therefore, be seen to be very importantfor treatment decisions in the medical field.

The present technology also generally relates to a method and system forquantitative detection of one or more target analytes in a biologicalsample by controlling the dynamic range of assay signals and, therefore,raw results. This technology allows for overcoming one or more drawbacksof the prior art and provide accurate and fast analyte detection.

According to one aspect of the technology, a method for controlling adynamic range of assay signals is provided. The method comprises thesteps of: (i) providing one or more target analytes in a sample; (ii)contacting the one or more target analytes with a mixture of aconjugated binding reagent and an unconjugated binding reagent, wherethe conjugated binding reagent and the unconjugated binding reagent arespecific to the one or more target analytes; (iii) measuring theinteraction between the one or more target analytes and the mixture ofthe conjugated binding reagent and the unconjugated binding reagent; and(iv) controlling a dynamic range of assay signals by adjusting a ratioof the conjugated binding reagent and the unconjugated binding reagentin the mixture.

In some embodiments, the method may further comprise the step ofdetermining a concentration of each of the target analytes. In yet moreembodiments, the method may further comprise the steps of adding one ormore conjugated analytes to the sample; and causing dilution of the oneor more target analytes. In yet more embodiments, the method may furthercomprise the steps of adding one or more unconjugated analytes to thesample; and causing dilution of the one or more target analytes.

In some embodiments, the conjugated binding reagent or the unconjugatedbinding reagent includes one or more of the following: an antibody, anantigen, an aptamer, a peptide, a protein, and an oligonucleotide, andany combinations thereof. The conjugated binding reagent may include abinding reagent coupled with a conjugate selected from a groupconsisting of: an enzyme, a protein, a peptide, a fluorophore, astreptavidin, an avidin, an antibody, an antigen, an aptamer, and anoligonucleotide, and any combinations thereof.

In some embodiments, the target analytes may include one or more of thefollowing: an antigen, an antibody, a nucleic acid, a carbohydrate, alipid, a peptide, a protein, a polymer, and any combinations thereof. Insome embodiments, the sample may include a biological fluid. In otherembodiments, the sample may include a non-biological fluid. In moreembodiments, the method may further include the step of quantitativelydetermining the one or more target analytes in the sample based onresults of the measuring of the interaction between the one or moretarget analytes and the mixture, and based on the controlling of thedynamic range of assay signals.

According to another aspect of this disclosure, there is providedanother method for controlling a dynamic range of assay signals. Themethod comprises the steps of: (i) providing one or more target analytesin a sample; (ii) contacting the one or more target analytes with amixture containing at least one binding reagent, wherein the bindingreagent is specific to the one or more target analytes; (iii) measuringthe interaction between the one or more target analytes and the mixture;(iv) adding one or more conjugated analytes to the sample to causedilution of the one or more target analytes; and (v) controlling adynamic range of assay signals by adjusting a ratio of the one or moreconjugated analytes in the mixture.

In some embodiments, the at least one binding reagent includes anunconjugated binding reagent. In certain embodiments, the at least onebinding reagent includes a conjugated binding reagent. In moreembodiments, the method may further include the step of quantitativelydetermining the one or more target analytes in the sample based onresults of the measuring of the interaction between the one or moretarget analytes and the mixture, and based on the controlling of thedynamic range of assay signals.

According to another aspect of this disclosure, there is providedanother method for controlling a dynamic range of assay signals. Themethod comprises the steps of: (i) providing one or more target analytesin a sample; (ii) contacting the one or more target analytes with amixture containing at least one binding reagent, wherein the bindingreagent is specific to the one or more target analytes; (iii) measuringthe interaction between the one or more target analytes and the mixture;(iv) adding one or more modified analytes to the sample; and (v)controlling a dynamic range of assay signals by adjusting a ratio of theone or more modified analytes in the mixture.

In some embodiments, the one or more modified analytes include moleculeshaving structures that are the same as structures within the one or moretarget analytes. For example, the one or more modified analytes includea subunit of at least one of the target analytes. In other embodiments,the method may further include the step of adding one or more conjugatedanalytes to the sample to cause dilution of the one or more targetanalytes. In certain embodiments, the at least one binding reagentincludes an unconjugated binding reagent. In some embodiments, the atleast one binding reagent includes a conjugated binding reagent. In yetmore embodiments, the method may further include the step ofquantitatively determining the one or more target analytes in the samplebased on results of the measuring of the interaction between the one ormore target analytes and the mixture, and based on the controlling ofthe dynamic range of assay signals.

According to yet another aspect of this disclosure, there is provided asystem for controlling a dynamic range of assay signals. The systemcomprises a container for providing one or more target analytes in asample and contacting the one or more target analytes with a mixture ofa conjugated binding reagent and an unconjugated binding reagent,wherein the conjugated binding reagent and the unconjugated bindingreagent are specific to the one or more target analytes. The systemfurther comprises a sensor configured to measure the interaction betweenthe one or more target analytes and the mixture of the conjugatedbinding reagent and the unconjugated binding reagent. The system furthercomprises a controller configured to control a dynamic range of assaysignals by adjusting a ratio of the conjugated binding reagent and theunconjugated binding reagent in the sample.

In some embodiments, the system may comprise an analyser configured todetermine a concentration of each of the target analytes. In certainembodiments, the sensor may include one or more of the following: acolorimetric sensor, a fluorimetric sensor, a photometric sensor, and aspectrophotometric device. In some embodiments, the analyser maycomprise a computing device operatively connected to the sensor. In someembodiments, the controller may comprise a computing device including atleast one processor and a memory, which stores processor executableinstructions, which when executed by the least one processor cause thesystem to make measurements by the sensor, change a ratio of themixture, and quantitatively determine the one or more target analytes.

In preferred embodiments of any one of the aforementioned aspects, theratio is selected from the group consisting a molar ratio, a weightratio and a volumetric ratio, and any combinations thereof.

Preferably, the ratio is a molar ratio.

Preferably, the ratio is a weight ratio.

Preferably, the ratio is a volumetric ratio.

According to preferred embodiments of any one of the aforementionedaspects, the biological sample is a blood sample.

The articles “a” and “an” are used herein to refer to one or to morethan one (i.e., to at least one) of the grammatical object of thearticle. By way of example, “an element” means one element or more thanone element. As used herein, the use of the singular includes the plural(and vice versa) unless specifically stated otherwise.

Throughout this specification, unless the context requires otherwise,the words “comprise,” “comprises” and “comprising” will be understood toimply the inclusion of a stated step or element or group of steps orelements but not the exclusion of any other step or element or group ofsteps or elements. Thus, use of the term “comprising” and the likeindicates that the listed elements are required or mandatory, but thatother elements are optional and may or may not be present. By“consisting of” is meant including, and limited to, whatever follows thephrase “consisting of”. Thus, the phrase “consisting of” indicates thatthe listed elements are required or mandatory, and that no otherelements may be present. By “consisting essentially of” is meantincluding any elements listed after the phrase, and limited to otherelements that do not interfere with or contribute to the activity oraction specified in the disclosure for the listed elements. Thus, thephrase “consisting essentially of” indicates that the listed elementsare required or mandatory, but that other elements are optional and mayor may not be present depending upon whether or not they affect theactivity or action of the listed elements.

Additional objects, advantages, and novel features will be set forth inpart in the detailed description, which follows, and in part will becomeapparent to those skilled in the art upon examination of the followingdetailed description and the accompanying drawings or may be learned byproduction or operation of the example embodiments. The objects andadvantages of the concepts may be realized and attained by means of themethodologies, instrumentalities, and combinations particularly pointedout in the appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagrammatic representation of a method for differentiatingand/or identifying cells or other components in a biological sampleaccording to an embodiment.

FIG. 2A is a diagrammatic representation of a further embodiment of amethod for differentiating and/or identifying cells or other componentsin a biological sample which uses antibodies to CD4 and CD8 to determineCD4+:CD8+ ratios in a sample to assess HIV progression.

FIG. 2B is a black and white reproduction of the colour representationin FIG. 2A.

FIG. 3A is a diagrammatic representation of an another embodiment of amethod for differentiating and/or identifying cells or other componentsin a biological sample which uses an antibody to a Gram-positivebacteria surface marker to determine a type of bacterial infection.

FIG. 3B is a black and white reproduction of the colour representationin FIG. 3A.

FIG. 4A is a diagrammatic representation of how the number of cells in asample affect the final signal strength.

FIG. 4B is a black and white reproduction of the colour representationin FIG. 4A.

FIG. 5A is a diagrammatic representation a method of the use of anantibody to CD molecules to determine the number of cells in a sample.FIG. 5A shows results using anti-CD4 antibodies to determine the numberof cells in a sample. In this example, a VL3 cell line with stableexpression of CD surface markers was used as the test sample. Y-axis isfluorescence; the X-axis is cell count (reciprocal)=1/(cell countx10e6). MFI is mean fluorescence intensity.

FIG. 5B shows results of using antibodies to CD19, a surface marker notexpressed by the VL3 Cell line, to determine if the effect demonstratedin FIG. 5A could be due to non-specific binding of the antibodies to thecells, or antibody aggregation. The Y-axis is fluorescence; the X-axisis cell count (reciprocal)=1/(cell count x10e6).

FIG. 6A is a diagrammatic representation of a method for quantitativedetection of one or more target analytes by controlling the dynamicrange of an assay according to an embodiment.

FIG. 6B is a black and white reproduction of the colour representationin FIG. 6A.

FIG. 7A is a diagrammatic representation of a method for quantitativedetection of one or more target analytes by controlling the dynamicrange of an assay which uses 100% biotinylated detection antibody with acontrolled ratio of labelled and unlabelled streptavidin.

FIG. 7B shows a method for quantitative detection by controlling thedynamic range of an assay by using biotinylated detection antibody witha controlled ratio of labelled and unlabelled streptavidin wherein aprolactin sandwich ELISA using a range of unconjugated streptavidinmixed with a horseradish peroxidase (HRP)-conjugated streptavidin wasundertaken. In FIG. 7B, the prolactin concentration (X-axis) is plottedagainst against the absorbance at 450 nm (Y-axis).

FIG. 7C shows the results of prolactin sandwich ELISA using a range ofunconjugated streptavidin mixed with a horseradish peroxidase(HRP)-conjugated streptavidin of FIG. 7B wherein the concentration ofunconjugated streptavidin (X-axis) is plotted against the absorbance at450 nm (Y-axis).

FIG. 8 is an example method for quantitative detection of one or moretarget analytes by controlling the dynamic range of an assay which usesan unlabelled primary detection antibody with a mixture of labelled andunlabelled secondary detection antibody.

FIG. 9 is a diagrammatic representation of a method of the presenttechnology by which the adjustment of labelled:unlabelled bindingreagent ratio adjusts the signal strength. Stated values is the ratio oflabelled to unlabelled detection antibody.

FIG. 10 illustrates experimental results with respect to the process ofFIG. 9 and in particular, human prolactin standard curves with adjustedratios of conjugated:unconjugated detection antibody using HRP-TMB. TheX-axis is the human prolactin concentration in pg/mL; the Y-axis isabsorbance at 450 nm. Curves A to F are the amount of labelled detectionantibody in the antibody mix as follows: A=1; B=0.8; C=0.6; D=0.4;E=0.2; F=0.

FIG. 11 is a diagrammatic representation of a method of controlling thelevel of detection signal in an immunoassay.

FIG. 11B is a black and white reproduction of the colour representationin FIG. 11A.

Some figures contain colour representations or entities. Colourillustrations are available from the Applicant upon request or from anappropriate Patent Office. A fee may be imposed if obtained from thePatent Office.

DETAILED DESCRIPTION

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by those of ordinary skillin the art to which the invention belongs. Although any methods andmaterials similar or equivalent to those described herein can be used inthe practice or testing of the present invention, preferred methods andmaterials are described. For the purposes of the present invention, thefollowing terms are defined below.

Each embodiment described herein is to be applied mutatis mutandis toeach and every embodiment unless specifically stated otherwise.

The embodiments can be combined, other embodiments can be utilized, orstructural, logical and operational changes can be made withoutdeparting from the scope of what is claimed. The following detaileddescription is, therefore, not to be taken in a limiting sense, and thescope is defined by the appended claims and their equivalents.

In order that the invention may be readily understood and put intopractical effect, particular preferred embodiments may be described byway of the non-limiting examples.

The following detailed description includes references to theaccompanying drawings, which form a part of the detailed description.The drawings show illustrations in accordance with example embodiments.These example embodiments, which are also referred to herein as“examples,” are described in enough detail to enable those skilled inthe art to practice the present subject matter.

Method and System for Identifying Cells in Biological Samples by AddingAntibodies Specific to Clusters of Differentiation

This present technology provides for a method and system fordifferentiating and/or identifying cells or other components(collectively referred to as “cells” for simplicity) in a biologicalsample such as a blood sample. Specifically, the method includes thesteps of incubating the sample with multiple antibodies or othermolecules such as aptamers (collectively referred to as “antibodies” forsimplicity), which bind specifically to certain surface markers of thecells. The methods described herein contemplates use of one or moreantibodies with one or more specificities. The number and types ofspecific surface markers can be preselected or predetermined such thateach of the surface markers is associated with a particular CD. Further,an antibody concentration in a sample, and particularly a blood sample,is determined either through calculation or measurement. In someembodiments, the antibody concentration can be predetermined or known.The sample is subsequently filtered by separating the cells from boundantibodies to produce a filtrate. Further, the antibody concentrationremaining in the filtrate is measured. Finally, the antibodyconcentrations before and after the filtration are compared to determinenumbers and/or types of the cells in the sample. It will be appreciatedthat a filtrate includes a fraction thereof.

FIG. 1 further illustrates this process. Specifically, it shows themethod where fluorescently labelled antibodies contact surface markersfor different types of cells in a sample. A known concentration oflabelled antibodies specific to surface markers on cells of interest areadded to a sample (Step A). The sample is incubated with antibodies toallow binding (Step B). At Step C, the sample is either (i) passedthrough a filter to remove cells and bound antibodies thus producing afiltrate containing unbound antibodies; or (ii) cells and boundantibodies are removed from the sample by sedimentation orcentrifugation to produce an aspirate containing unbound antibodies.Following Step C, the filtrate is introduced to a surface with regionscontaining immobilised surface proteins (Step D). The filtrate isincubated to permit antibodies to bind immobilised antigens (Step E).After washing, light emittance from immobilised labelled-antibodies ismeasured and an antibody concentration in the filtrate is calculated(Step F). Finally, the number of each type of cell is calculated fromthe difference in antibody concentration pre- and post-filtration.

FIG. 2 (A and B) shows a more particular example, which uses antibodiesto CD4 and CD8 to determine CD4+:CD8+ ratios in a sample to assess HIVprogression. FIG. 3 (A and B) shows another example, which uses anantibody to Gram-positive bacteria surface marker to determine a type ofbacterial infection. FIG. 4 (A and B) shows how the number of cells inthe sample affect the final signal strength. Panel A of each of FIG. 4Aand 4B shows that when there is a low number of target cells in thesample, this leads to a small loss of antibodies in the filtrate andtherefore a high signal. Panel B shows that when there is a high numberof target cells in a sample, this lead to a high loss of antibodies inthe filtrate and thus a low signal. As can be seen from FIG. 4 A and Bcollectively, the higher the number of target cell in the sample, thehigher the number of antibodies that are removed at the filtrationstage, and thus a lower signal will be produced.

The system for differentiating and/or identifying cells includes threemain components: a sampling module for receiving and incubating sampleswith antibodies, a filter for filtering the sample and an analyser foranalysis of the filtrate. The analyser may include one or more sensorsoperatively coupled to a computing device such as a personal computer,laptop computer, server or the like. The computing device includes atleast one processor and at least one memory, which storesprocessor-executable instructions. When these instructions areimplemented by the processor, it implements one or more steps of themethods as described herein.

According to some embodiments of this disclosure, the filter may includea membrane with a pore size less than 2 micrometres to remove all thecells or substantially all the cells from a sample and more preferably,a blood sample. In other embodiments, a magnetic separation system canbe used instead of the filter or any other apparatus of removing thecells along with marker-bound antibodies from the blood sample. In otherembodiments, the cells may be removed through sedimentation,centrifugation, or through the use of antibodies to immobilize, orremove the target cells.

According to some embodiments of this disclosure, either the unboundantibodies remaining in the filtrate or the antibodies bound to thecells, either when bound or by after treatment to unbind them from thecell surface, may be conjugated to one or more molecules that wouldfacilitate further analysis such as a reporter. The conjugated moleculesmay include enzymes, such as horse radish peroxidase, which can catalysea measurable change in a developer fluid. In other embodiments, theconjugated molecules may include a fluorescent probe, which can bemeasured through light emission. In yet other embodiments, theconjugated molecules may include biotin, to which a further reportermolecule can be attached though a high affinity binding process using abiotin-streptavidin/biotin/avidin system. In some embodiments,unconjugated antibodies can be used. In yet more embodiments, asecondary reporter can be applied. For example, a secondary antibodylabelled with an enzyme or reporter molecule is utilized in case of theuse of unconjugated antibodies.

The term “reporter” means a molecule, which, by its chemical nature,provides an analytically identifiable signal that allows the detectionof a predetermined antigen. Detection may be either qualitative orquantitative. Some examples of reporters include enzymes, fluorophores,gold or radionuclide containing molecules (i.e., radioisotopes). In thecase of enzyme immunoassay, an enzyme is conjugated to the second orthird immunoglobulin, generally by means of glutaraldehyde or periodate.Other types of enzymes that can be used includes horseradish peroxidase,glucose oxidase, β-galactosidase, and/or alkaline phosphatase.

In some embodiments of the present disclosure, a whole blood sample isincubated with a mixture of a predetermined amount of labelledantibodies against a range of surface markers to identify, for example,red blood cells, platelets, and/or to differentiate white blood cells.The blood sample can be further incubated to allow the antibodies tobind to surface antigens. In other embodiments, a particular fraction ofwhole blood may be analysed, such as separated white blood cells.

In some embodiments of the present disclosure, the system may include astructure containing discrete regions to which surface markers, againstwhich the antibodies have been raised, are bound. A non-limiting exampleof such a structure is a structure made from a suitable plasticsmaterial such as microtiter plate or a cuvette. In this case, thefiltrate can be incubated inside the structure allowing the remainingantibodies, those that have not bound to the cells prior to thefiltration, to bind to immobilized surface markers. Following theincubation, the structure can be washed to remove all unbound componentsof the filtrate. If unconjugated antibodies are utilized, a furtherincubation with a solution containing a secondary reporter molecule(e.g., a labelled secondary antibody, streptavidin-conjugated enzyme, orprobe) may be required. If an enzyme, such as horseradish peroxidase(HRP), is used as a labelled secondary antibody, a developer solutionmay be required to pour into the structure. The developer solution mayrelate to a 3,3′,5,5′-Tetramethylbenzidine (TMB), which may undergo ameasurable colour change, the rate of which is dependent on the amountof enzyme. Accordingly, the amount of bound antibodies can be determinedbased on the extent of colour change measured. In other embodiments,developer solutions can include colorimetric, fluorescent, and/orchemiluminescent solutions.

As discussed above, the difference in antibody concentrations prior tofiltration and after filtration can be used to calculate theconcentration and/or ratio of the surface markers in the original bloodsample. The concentration and/or ratio of the surface markers, in turn,can serve a basis for calculation of the number of cells of each type,including differentiated white blood cells.

In yet another embodiment of the present technology, antibodies topathogen surface markers are used to identify and quantify pathogens ina sample. In still another embodiment of this disclosure, surfacemarkers to mycoplasma cells can be used to detect mycoplasma growth incell lines.

In some embodiments of the present disclosure, the system foridentifying cells in a blood sample may include a biosensor. Thebiosensor is an analytical device that can be used for the analysis ofanalyte. The biosensor may comprise a sensitive biological element(e.g., tissue, microorganisms, organelles, cell receptors, enzymes,antibodies, nucleic acids, whole blood or a fraction thereof etc.), abiologically derived material or biomimetic component that interactswith the analyte under study. The biologically sensitive elements canalso be created by biological engineering. The biosensor furthercomprises a transducer or a detector (e.g., a physicochemical, optical,piezoelectric, or electrochemical device) that transforms a signalresulting from an interaction of the analyte with the biological elementinto another signal that can be more easily measured and quantified. Thebiosensor further comprises a biosensor reader device with associatedelectronics (e.g., a computing device) that are primarily responsiblefor the display of the results in a user-friendly way.

In some embodiments, this technology may be incorporated into a membranebased device using a colour reporting method, such as colloidal gold, toprovide rapid measurements of the presence or absence of one or morecomponents in a sample, e.g., pathogen, or the levels of one of moreelements in a sample, e.g., CD4+ and CD8+ cells (see FIG. 2).

According to various embodiments, the present technology can be alsoconfigured to determine diseases of a subject, an individual or ananimal, whose samples and preferably, fluid samples were tested andanalysed. Moreover, the present technology may provide automaticrecommendations, suggestions, or plans for treating identified diseases.Non-limiting examples of treatment modalities include radiotherapy,surgery, chemotherapy, hormone ablation therapy, pro-apoptosis therapy,immunotherapy, phototherapy, cryotherapy, toxin therapy, treatment withan anti-infective drug or pro-apoptosis therapy. One of skill in the artwould know that this list is not exhaustive of the types of treatmentmodalities. Diseases can be determined based on the results ofdifferentiating/identifying of cells in samples as described herein. Forexample, determination of white blood cell count using the methods ofthis disclosure could be used to determine if an individual has aninfection leading to treatment with antibiotics. In another embodiment,the determination of red blood cell count using the methods of thisdisclosure can be used to determine if an individual is anaemic andneeds to be treated, for example, with iron supplements. In yet anotherembodiment, the determination of decreased white or red blood cell countmay be a consequence of treatment with certain drugs, for example,clozapine. Therefore, the choice of treatment can also depend on a cellcount. Determination of blood cell count and cell count in otherbiological samples can, therefore, be seen to be very important fortreatment decisions in the medical field. In preferred embodiments, themethods described herein further include the step of treating a subject.

The terms “patient,” “subject,” “host” or “individual” usedinterchangeably herein, refer to any subject, particularly a vertebratesubject, and even more particularly a mammalian subject, for whomtherapy or prophylaxis is desired. The term “subject” is inclusive of ahuman mammalian subject and a non-human mammalian subject.

As used herein, the terms “treatment,” “treating,” and the like, referto obtaining a desired pharmacologic and/or physiologic effect. Theeffect may be therapeutic in terms of a partial or complete cure for adisease or condition and/or adverse effect attributable to the diseaseor condition. These terms also cover any treatment of a condition ordisease in a mammal, particularly in a human, and include: (a)inhibiting the disease or condition, i.e., arresting its development; or(b) relieving the disease or condition, i.e., causing regression of thedisease or condition.

The use of an antibody to CD molecules to determine the number of cellsin a sample is shown in FIG. 5A and 5B. A VL3 cell line with stableexpression of CD surface markers was used for the experiment.Fluorescently labelled anti-CD4 antibodies at a concentration of 0.0008mg/ml were incubated with samples of cells at a range of cellconcentrations, from 4.6x10e6, to 0.009x10e6 cells per ml. Followingincubation to allow the antibodies to bind to the CD4 molecules on thesurface of the cells, the samples were centrifuged to remove the cells.The supernatant was removed and the amount of antibody remaining in thesupernatant was assayed. This was done by adding antibody-binding beadsto the supernatant and incubating to allow the remaining antibodies tobind to the beads. The beads were then run through a BD FACSDiva flowcytometer to measure the fluorescence. As shown in FIG. 5A there was aclear inverse relationship between the number of antibodies present inthe supernatant, and the number concentration of cells in the sample.Beyond the lower limit of 1.4x10e5 cells per ml (shown by arrow), thenumber of cells could not be determined in this experiment.

The process was repeated using antibodies to CD19, a surface marker notexpressed by the VL3 Cell line, to determine if this effect could be dueto non-specific binding of the antibodies to the cells, or antibodyaggregation. Referring to FIG. 5B, there is a small reduction in thesignal at very high cell concentrations, but not sufficient to interferewith the result obtained through specific binding of antibodies toexpressed CD molecules. This data supports that the method is effectivein determining the number of cells expressing a particular marker,present in a sample and the suitability of this method indifferentiating and quantifying cells types present in a sample.

Those skilled in the art will appreciate that the present technologyallows for identifying cells not only in blood samples, but also anyother biological fluids, tissue samples, food, water, and culturedcells. The disclosed technology provides a fast and accurate low costmethod and system which can be incorporated into a portable and/ordisposable unit to provide a fast, field/point-of-care-based methodapplicable for blood cell count and differentiation for diagnostics,health monitoring, blood typing and monitoring of HIV progression,distinguishing between infections of viral or bacterial origin, pathogendetection and identification, diagnostics based on biological fluid andtissue samples, utilization in food industry, agricultural applications,veterinary applications, water quality testing, and/or detectingmycoplasma contamination in cultured cell lines.

It will be appreciated that the biological material may be an isolatedbiological material that may or may not be purified. By “isolated” ismeant material that is substantially or essentially free from componentsthat normally accompany it in its native state, or from componentspresent during its production when purified or produced by syntheticmeans. Thus, the term “isolated” also includes within its scope purifiedor synthetic material. As used herein, the term “purified” refers tomaterial (e.g., a blood sample, a fluid sample) that is substantiallyfree of cellular components or other contaminating material from thesource from which the material is derived. “Substantially free” meansthat a preparation of a material is at least 10%, 20%, 30%, 40%, 50%,60%, 70%, 80%, 90%, 95%, 96%, 97%, 98%, 99% pure.

Method and System for Controlling Dynamic Range of Assay Quantificationfor Analyte Detection

The present technology also provides for an assay analysis based onimmunoassay methods, where a concentration of analyte in a sample isdetermined in reliance to intensity of detection signal. These methodsare generally applicable for detection and/or quantification of analytessuch as an antigen, antibody, protein, and nucleic acids in samples suchas biological fluids (e.g., blood) or non-biological fluids. The samplesmay be isolated and may or may not be purified.

The term “assay,” as used herein, refers to an analytical detectionmethod including, but not limited to, enzyme-linked immunosorbent assay(ELISA), radioimmunoassay (RIA), chemiluminescent assay, bioluminescentassay, fluoroimmunoassay, protein microarray, DNA microarray, RNAmicroarray, and/or protein biochip assay.

The term “target analyte,” as used herein, refers to a biochemicalsubstance to be detected or quantified in a biological sample and maycomprise one or more of the following: an antigen, antibody, protein,lipid, carbohydrate, and nucleic acids, and any combinations thereof.

The term “solid phase,” as used herein, refers to planar or nonplanarsolid support surfaces used in immunodetection methods and may compriseone or more of the following: a polystyrene microtiter plate, amicrosphere, a bead, a membrane, a polymer, copolymer, a cross-linkedpolymer, and the like.

The term “binding reagent,” as used herein, refers to a biochemicalsubstance capable of reacting with the target analyte or used fordetecting the presence of the target analyte in a sample. The bindingreagent may refer to an antigen, an antibody, a protein, and/or anoligonucleotide.

The term “detection signal” or simply “signal,” as used herein, refersto a measurable signal produced by a labelled analyte or conjugatedanalyte or labelled binding reagent or conjugated binding reagent. Thedetection signal may be measured using, for example, one or more of thefollowing methods: a photometric method, spectrophotometric method,radiometric method, and fluorometric method. Those skilled in the artwill appreciate that other methods, such as mass spectrometry, can bealso used for measuring the detection signal.

A dynamic range (or “detection range”) of assay results (signals) can bedefined as the lowest concentration to the highest concentration of ananalyte (also referred herein to as “target analyte”) that can beaccurately detected by the assay. The concentration of the analyte isgenerally required to be present within the dynamic range or detectionrange of the assay in order to be measured. The dynamic range of assayresults can be predetermined or dynamically changed.

Generally, the present technology relates to a method for quantitativedetection of one or more target analytes by controlling the dynamicrange of an assay. The method comprises the following steps: i)providing the one or more target analytes in the biological sample; ii)contacting the one or more target analytes with a mixture of at leastone conjugated binding reagent and at least one unconjugated bindingreagent, wherein the at least one conjugated binding reagent and the atleast one unconjugated binding reagent are specific to the one or moretarget analytes; iii) measuring the interaction between the one or moretarget analytes and the mixture of the at least one conjugated bindingreagent and the at least one unconjugated binding reagent; and iv)controlling a dynamic range of assay signals by adjusting a ratio of theat least one conjugated binding reagent and the at least oneunconjugated binding reagent in the mixture.

The term “ratio” refers to a ratio in the standard sense; the amount ofone element relative to the amount of another another element. Thiscould be expressed by molarity, weight or volume. Preferably, the ratiois selected from the group consisting of a molar ratio, a weight ratioand a volumetric ratio, and any combination thereof. In preferredembodiments, the ratio is a molar ratio. In other preferred embodiments,the ratio is a volumetric ratio. In yet other preferred embodiments theratio is a weight ratio.

It should be clear that the above method may have more limiting exampleimplementations as discussed below. In some embodiments, the method isfocused on providing a conjugated agent and an unconjugated agent in asample with target analytes so that these agents compete with each otherto bind to the analyte. Accordingly, providing the conjugated andunconjugated agents can reduce assay signals, thereby changing a dynamicrange.

In other embodiments, the method is focused on using conjugated orunconjugated analytes, which are added to a sample to dilute the targetanalytes, which ultimately leads to the change of the assay signal. Forexample, the conjugated analyte could bind to an antibody bound to asolid phase, which has a fluorophore that is quenched by binding to theconjugated analyte. By having conjugated and unconjugated analytes, theamount of quenching for a given concentration or amount of analytes canbe reduced, thereby changing the dynamic range.

Alternatively, in other embodiments, only one or more conjugatedanalytes and a binding reagent specific to the one or more targetanalytes is needed. The conjugated analytes are bound with a marker thatis modified or otherwise activated or deactivated as binding takes placeincreasing or decreasing a signal (such as fluorescence) from theconjugated analyte. As the conjugated analytes bind to the reagent, thesignal from the conjugated analytes increases or decreases. The ratiobetween conjugated analyte and unconjugated analyte (in the sample andpossibly with addition of additional unconjugated analyte as well)determines the magnitude of the increase or decrease in the signal.

In other embodiments, rather than conjugated analyte, one or moremodified analytes (which could be simply a molecule containing some ofthe same structures as the target analyte) could be used. Both modifiedanalytes and target analytes (from the sample with or without additionof regular analyte) bind to the one or more first reagents. One or moresecondary conjugated reagents can then be added, each of which bindsonly to either one or more of the target analytes or one or more of themodified analytes. The ratio between modified analyte and target analytedetermines the magnitude of the increase or decrease in the signal. Insome embodiments, the one or more modified analytes are molecules, whichcontain structures that are the same as structures within the targetanalytes, for example, at least some of the modified analytes may be orinclude a subunit of at least one of the target analytes. In someembodiments, the target analyte could be a protein. In some embodiments,the first reagent could be an antibody, which binds to both the targetanalyte and modified analyte conjugated reagent, whilst the secondconjugated reagent is an antibody, which binds only to the targetanalyte, but not the modified analyte. In some embodiments, theconjugated reagent is conjugated with a fluorophore for fluorescentdetection.

In other embodiments, there are one or more target analytes and one ormore modified analytes, which compete to bind to a conjugated reagent.Only binding of either target analyte or modified analyte causes theactivation or de-activation of the conjugated marker (e.g., quenching ofa fluorophore). Hence, the ratio between the modified analyte and targetanalyte determines the magnitude of the increase or decrease in thesignal.

The term “conjugated,” as used herein, means connected with a markerthat leads to a signal measurable with a sensor whether a direct signalproducing marker (such as a fluorophore) or a chemical group, which canbe used to attach a signal producing group such as a biotin orstreptavidin group.

It should be noted that binding of an analyte to a reagent prevents orreduces the number of analytes that can bind to that reagent so theanalytes compete to bind to a particular reagent.

In an embodiment, the present technology may include the followingexample method for quantitative detection of one or more target analytesby controlling the dynamic range of an assay. The method comprises thesteps of: i) providing a solid phase immobilized with the one or moremolecules, which bind specifically to the target analytes; ii)contacting the solid phase with the sample, in which the concentrationor presence of the one or more target analytes is to be measured; iii)introducing a binding reagent, which will contain a mixture of reagents,which will be either conjugated or unconjugated to a reporter molecule,such as a fluorophore; iv) allowing to compete the conjugated andunconjugated binding reagents in order to bind to the immobilized targetanalyte. The amount of fluorophore can be measured by detecting lightemission. Further, the concentration of target analyte can be calculatedbased on these measurements. The method may further include the stepsof: v) controlling a signal level (and thus dynamic range) throughadjustment of the ratio of conjugated and unconjugated binding reagents.This process is further illustrated in FIG. 6. Specifically, FIG. 6shows a sandwich ELISA using 4:6 ratio of fluorophoreconjugated:unconjugated detection antibody to lower the signal produced.

In one or more embodiments, the conjugated binding reagent or theunconjugated binding reagent includes an antibody, an antigen, anaptamer, a protein, and/or an oligonucleotide. In certain embodiments,the conjugated binding reagent includes a binding reagent coupled with aconjugate selected from a group consisting: an enzyme, a protein, afluorophore, a streptavidin, an avidin, an antibody, an antigen, anaptamer, and an oligonucleotide. In certain embodiments, the conjugatedbinding reagent is conjugated to a label, which allows detecting theconjugated binding reagent bound to a target analyte. Labels may includeenzymes capable of producing a measurable response (e.g., visible colourchange) in the presence of corresponding substrates. The enzymes mayinclude, but not limited to, horseradish peroxidase (HRP), alkalinephosphatase (AP), luciferase, beta-galactosidase, and glucose oxidase.Labels or conjugates used for detection of binding reagents may alsocomprise carrier molecules such as a fluorophore, streptavidin, andavidin. Other example labels could be also used to allow detection of anelectronic or radiographic signal. In various embodiments, targetanalytes include one or more of the following: an antigen, an antibody,a nucleic acid, a carbohydrate, a lipid, a protein, a polymer, and anycombinations thereof.

In an embodiment, the binding reagent may comprise a primary bindingmolecule that directly binds to an analyte such as a primary antibody.In another embodiment, the binding reagent may comprise a secondarybinding molecule that binds to a primary binding molecule such as asecondary antibody. This embodiment is further illustrated by FIG. 8that shows an example method, which uses an unlabelled primary detectionantibody with a mixture of labelled and unlabelled secondary detectionantibody.

In yet another embodiment, the binding reagent is capable of reactingwith another element allowing measurement in the assay. For example, theuse of a biotinylated antibody that binds to streptavidin conjugated toan element allows the measurement. This embodiment is furtherillustrated generally by FIG. 7. FIG. 7A that shows an example method,which uses 100% biotinylated detection antibody with a controlled ratioof labelled and unlabelled streptavidin. The mix of HRP-conjugated andunconjugated streptavidin to control assay range is described below andshown in FIG. 7B and 7C. The purpose of this experiment was todemonstrate that the signal, and therefore assay range can be modifiedby mixing the HRP-conjugated streptavidin with unconjugatedstreptavidin, which will compete for binding with the HRP-conjugatedstreptavidin to the biotinylated detection antibody. And to lower thesignal produced, while maintaining the standard curve. The range oftarget concentrations was run using a range ofstreptavidin:HRP-streptavidin ratios.

A standard ELISA was performed using Human Prolactin across a wide rangeof concentration levels, from 49 pg/ml to 5 ug/ml. The assay wasperformed using a capture antibody coated plate, recombinant prolactinas a target, biotinylated detection antibody, HRP-conjugatedstreptavidin and TMB as a developer fluid, stopped with 2M H₂SO₄.Astandard protocol was used as follows: The plate was coated with acapture antibody and subsequently washed with a phosphate bufferedsaline—Tween 20 solution (PBST). The plate incubated for 2 hours withtarget in 1% BSA and washed with PBST. The plate incubated for 1 hourwith a biotinylated detection antibody and washed with PBST. The plateincubated with HRP-conjugated streptavidin (with a range on unconjugatedstreptavidin added), followed with a wash step with PB ST (as above).The chromogenic substrate 3,3′,5,5′-Tetramethylbenzidine (TMB) wasadded, the reaction stopped after 10 minutes with 2M H₂SO₄ and theabsorbance read at 450 nm.

The data shows that as that as the amount of unconjugated streptavidinis increased, the signal level is reduced. As shown in FIG. 7B, with 0unconjugated streptavidin, the curve levels off with a prolactinconcentration of 1.56 ng, and only concentrations below this can bedifferentiated. With the addition of 73 ng/ml of unconjugatedstreptavidin, the signal is reduced and the flattening of the curve doesnot occur until the prolactin concentration reaches 1.25 ug, allconcentrations below can now be differentiated. As the amount ofunconjugated streptavidin is increased, the signal level is furtherreduced, delaying the plateau, and thus increasing the concentration oftarget that can be determined by the assay. When the concentration ofunconjugated streptavidin is increased to 225 ng/ml the developmentappears to have been completely prevented, indicating that insufficientHRP-conjugated streptavidin has been able to bind to the biotinylateddetection antibody. By plotting each target concentration against theconcentration of unconjugated streptavidin used, the amount ofunconjugated streptavidin needed to adjust the assay range for aparticular target can be determined (FIG. 7C).

As already discussed above, the mixture includes a conjugated bindingreagent and an unconjugated binding reagent, specific to one or morepredetermined target analytes. Different ratios of conjugated andunconjugated binding reagents in the mixture can be used for preciselycontrolling the detection range of target analytes immobilized on thesolid phase. For example, FIG. 9 shows a process, by which theadjustment of labelled:unlabelled binding reagent ratio adjusts thesignal strength. FIG. 10 illustrates experimental results with respectto the process of FIG. 9, which show that the signal strength can beadjusted by changing the ratio of conjugated:unconjugated detectionantibody.

The conjugates or labels provide a measurable response or detectionsignal in the presence of substrate, thereby representing a positiveinteraction between the binding reagent and target analyte. Thedetection signal may comprise a colour change, fluorescent signals,and/or chemiluminescent signals, which can be measured by photometric,spectrophotometric or colorimetric methods. The concentration of thetarget analyte can be accurately determined based on a level ofdetection signal (e.g., a level of colour change by an enzyme conjugatereflects the concentration of corresponding target analyte).

In an embodiment, the method comprises the use of a binding reagentmixture comprising HRP-conjugated antibody and unconjugated antibodywithin an immunoassay. The HRP-conjugated antibody competes with theunconjugated antibody for binding sites on a target analyte that isimmobilized onto a solid support. The control of HRP-conjugated antibodyto unconjugated antibody ratio allows for precise controlling detectionsignal dampening, which in turn, allows enhancing the dynamic range ofthe assay in order to cover the concentration range of the targetanalyte likely to be present in the sample or immobilized to the solidsupport (see also FIG.10).

The interaction between the reagent mixture and target analyte includescompetitive binding between the conjugated and unconjugated bindingreagents to the binding sites on target analytes immobilized on thesolid phase (see also FIG. 6).

In yet another exemplary embodiment, the target analyte comprises anantigen immobilized onto a solid phase support. The mixture may includean unconjugated binding reagent having an antibody capable ofspecifically binding to the immobilized antigen and a conjugated bindingreagent having an enzyme-labelled antibody capable of binding to theimmobilized antigen. Upon adding the mixture to the solid phasecomprising target antigen, the enzyme-labelled antibody competes withthe unlabelled antibody for binding sites on the surface of the targetantigen.

The concentration of multiple analytes may differ within a biologicalsample. For example, thyroid-stimulating hormone (TSH) is normallypresent in the range of pg/ml, while luteinizing hormone (LH) andfollicle-stimulating hormone (FSH) are present in the range of ng/ml, ina biological sample. In another example, for testing Trisomy 23, Down'ssyndrome, the concentration of human chorionic gonadotropin (hCG),estriol (E3), and alpha-fetoprotein (AFP) are measured. In a testsample, hCG is normally present in the range of mg/mL, E3 is present inthe range of ng/mL, and AFP is present in the range of pg/mL. Thevariation in a concentration range of different analytes within a samplerenders multiplex assays more challenging due to consequent variation inthe dynamic range of the assay. Therefore, quantitative assay methodsrequire balanced measurements and the need to control the reactivity ofbinding reagents, for analysing a sample with higher concentration ofanalytes and for analysing a sample containing multiple analytes atsignificantly different detection ranges.

According to yet more embodiments, the technology of the presentdisclosure provides for a method of controlling the level of detectionsignal in an immunoassay. The level of a detection signal from eachanalyte can be precisely controlled by using known concentrations ofconjugated and unconjugated binding reagents at different ratios(consider FIG. 11). The method allows for accurate quantification ofmultiple target analytes at wide ranges of concentrations in a sampleand can be employed in singleplex assays, as well as in multiplex ormultiple-singleplex assays. The method further allows balancing and/oroptimizing of the ratio of conjugated binding reagent to unconjugatedbinding reagent according to a standard or expected concentration rangeof each analyte within a sample (see also FIG. 11). The sample isintroduced to a solid phase with antibodies for two target analytes ofdifferent concentrations (Step 1). The first target analyte is at a highconcentration whereas the second target analyte is at a lowconcentration. The target analytes bind to antibodies (Step 2).Detection antibodies are introduced to the solid phase wherein 25% isconjugated for analyte 1, 100% is conjugated for analyte 2 (Step 3).Detection antibodies bind to immobilised target analytes (Step 4) andsubsequently the signal from analyte 1 is equalised to signal fromanalyte 2 to allow simultaneous analysis (Step 5).

By changing the assay signal, greater control of readout of singleplexor multiplex tests can be exercised. Accordingly, applying the presenttechnology principles to multiplex tests, it is easier to obtainmultiple results at once and have a longer development period.Ultimately, this leads to a more precise measurement of concentration.In one embodiment, this would allow the assay signals of various thyroidbiomarkers, TSH, T3, and T4 to be changed to be the same (or have verysimilar ranges) even though concentrations are different. By knowing theconjugated vs. unconjugated levels of antibody, it is possible todetermine the concentrations of each antibody individually in themixture.

In an alternate embodiment, the present technology relates to a methodfor controlling the dynamic range of an assay by controlling the levelof detection signal. The method comprises the steps of: i) providing asolid phase immobilized with a binding reagent, specific for a targetanalyte; ii) contacting the solid phase with a mixture of a samplecomprising target analyte and a conjugated analyte; iii) incubating thesolid phase in contact with the mixture under optimum conditions forinteraction; and iv) measuring the interaction between the immobilizedbinding reagent and the mixture, wherein dynamic range of the assay iscontrolled by adjusting the ratio of the sample analyte to theconjugated analyte in the mixture. The target analytes present in thesample can be quantitatively determined by controlling the dynamic rangeof the assay.

For example, the target analyte to be tested may comprise a protein.Further, the mixture may include a sample containing target proteinmixed with a known concentration of the same protein conjugated with anenzyme such as HRP. The mixture further reacts with a solid phaseimmobilized with an antibody specific to the protein, under optimalconditions for protein-antibody binding. The enzyme labelled proteincompetes with target protein in the sample for binding to target siteson immobilized antibody and the difference in binding the proteins inthe mixture is measured by detection signals produced by the enzyme uponadding a suitable substrate.

The level of detection signals can be controlled by optimizing the ratioof conjugated analyte to target analyte in the sample. For example, thehigher concentration of conjugated analyte than target analyte in asample results in increased binding of conjugated analyte to theimmobilized binding reagent, thus increasing detection signals.Similarly, a ratio of the mixture containing a higher concentration ofthe target analyte and a lower concentration of conjugated analyteresults in increased binding of target analyte to the immobilizedbinding reagent, thus providing reduced detection signals. For instance,the detection signal may comprise colour changes of added substrate dueto the enzymatic activity of the conjugate. The change in intensity ofcolour indicates the difference in binding among the target analyte andconjugated analyte to the immobilized binding reagent or detectionreagent.

In yet another embodiment, the present technology provides a system forquantitative detection of one or more analytes by controlling thedynamic range of an immunoassay. The system comprises a container or amixer for providing target analytes to biological sample and contactingthe target analytes with a mixture of a conjugated binding reagent andan unconjugated binding reagent. In some embodiments, the container ormixer can allow reacting the mixture having a conjugated binding reagentand an unconjugated binding reagent at different predetermined ratioswith one or more analytes immobilized on a solid phase. However, thesolid phase is not required to all embodiments to all embodimentsdescribed herein, and accordingly the present disclosure is not limitedto the use of the solid phase.

The system further includes a sensor configured to measure theinteraction between the one or more target analytes and the mixture ofthe conjugated binding reagent and the unconjugated binding reagent. Forexample, the sensor can determine a first concentration of theconjugated binding reagent reacting with the analytes on the solid phaseand a second concentration of the unconjugated binding reagent reactingwith the analytes on the solid phase.

The system further includes controller configured to control a dynamicrange of assay signals by adjusting a ratio of the conjugated bindingreagent and the unconjugated binding reagent in the mixture. The systemmay further include an analyser configured to determine a concentrationof each of the target analytes. For example, the analyser canquantitatively determine one or more target analytes by analysing thefirst concentration and second concentration of the binding reagents foreach ratio of the mixture.

The sensor may comprise a colorimetric, fluorimetric, photometric,and/or spectrophotometric devices adapted for measuring or quantifyingdetection signals produced by the binding reagents interacting withtarget analytes. The controller may also comprise a computing deviceoperatively connected to the sensor of the system. In some embodiments,the computing device includes at least one processor and a memory, whichstores processor executable instructions, which when executed by theleast one processor cause the system to make measurements by the sensor,change a ratio of the mixture, and quantitatively determine the one ormore target analytes. In some embodiments, the analyser also includes acomputing device such as a personal computer or a laptop. In yet moreembodiments, the controller and analyser can be combined together in asingle device. For example, one computing device can be used as thecontroller and the analyser.

The container may comprise a microtiter plate, microstrip, glass tube,and/or similar devices adapted to receive or mix reagents with analytesor sample containing one or more analytes.

In an embodiment, the analyser determines the concentration of a targetanalyte in a sample based on the difference between multipleconcentration values of binding reagents interacting with the solidphase, for different predetermined ratios of conjugated and unconjugatedbinding reagent in the mixture. The dynamic range of the assay iscontrolled or modified by adjusting the ratios of the mixture containingbinding reagents. Thus, the sensitivity of the assay is controlled fordetermining the concentration of one or more analytes in the sample.

The methods and systems of the present disclosure relating toquantitative determination of analytes by controlling the level ofdetection signal or controlling the dynamic range of an assay can beemployed in a variety of immunoassays (e.g., bead-based assay,microtiter plate-based assay or microstrip based assay), microarrays(e.g., protein microarray, DNA microarray, RNA microarray), proteinbiochip assay, antibody array, and in assays performed usingmicrofluidic devices. These assays may typically be biological assays,but not necessarily, as the principle methods of this disclosure may beapplied to any molecular or other chemical detection.

According to certain embodiments, the present technology can be alsoconfigured to determine diseases of a subject, whose fluid samples weretested and analysed using the methods described herein. For example,measurement of troponin and B-type natriuretic peptide (BNP) biomarkersusing the methods disclosed herein could lead to a determination ofcongestive heart failure and subsequent treatment with warfarin.Moreover, the present technology may provide automatic recommendations,suggestions, or plans for treating identified diseases. In particular,various diseases can be determined based on the results of quantitativedetection of one or more target analytes in biological samples asdescribed herein.

Thus, methods and systems for differentiating and/or identifying cellsor other components in biological samples have been described andmethods and systems for quantitative detection of one or more targetanalytes in a biological sample by controlling the dynamic range ofassay signals have been described. Although embodiments have beendescribed with reference to specific example embodiments, it will beevident that various modifications and changes can be made to theseexample embodiments without departing from the broader spirit and scopeof the present application. Accordingly, the specification and drawingsare to be regarded in an illustrative rather than a restrictive sense.

As used herein, by “synthetic” is meant not naturally occurring but madethrough human technical intervention. In the context of syntheticproteins, peptides and nucleic acids, this encompasses moleculesproduced by recombinant, chemical synthetic or combinatorial techniquesas are well understood in the art.

The disclosure of every patent, patent application, and publicationcited herein is hereby incorporated herein by reference in its entirety.

The citation of any reference herein should not be construed as anadmission that such reference is available as “Prior Art” to the instantapplication.

Throughout the specification the aim has been to describe the preferredembodiments of the invention without limiting the invention to any oneembodiment or specific collection of features. Those of skill in the artwill therefore appreciate that, in light of the instant disclosure,various modifications and changes can be made in the particularembodiments exemplified without departing from the scope of the presentinvention. All such modifications and changes are intended to beincluded within the scope of the appended claims.

1. A method for differentiating cells in a biological sample, the methodcomprising: contacting the biological sample with marker-specificmolecules against at least one surface marker of the cells, wherein themarker-specific molecules are associated with a first count parameter;allowing the cells in the biological sample to bind to themarker-specific molecules to produce bound marker-specific molecules;filtering the biological sample by removing the cells and the boundmarker-specific molecules from the biological sample to generate afiltrate; determining, by a sensor or an analyser, a second countparameter of the marker-specific molecules in the filtrate; andcalculating, by a computing device or the analyser, a number of thecells in the biological sample based on the difference between the firstcount parameter and the second count parameter.
 2. The method of claim1, wherein the first count parameter includes a first concentration ofthe marker-specific molecules, and wherein the second count parameterincludes a second concentration of the marker-specific molecules.
 3. Themethod of claim 1, wherein the first count parameter includes a firstcount number of the marker-specific molecules, and wherein the secondcount parameter includes a second count number of the marker-specificmolecules.
 4. The method of 1, wherein the marker-specific moleculesinclude one or more antibodies of at least one type.
 5. The method ofclaim 1, wherein the marker-specific molecules include one or moreaptamers of at least one type.
 6. The method of claim 1, wherein each ofthe surface markers is associated with a distinct cluster ofdifferentiation.
 7. The method of claim 1, further comprisingidentifying one or more types of the cells based on the differencebetween the first count parameter and the second count parameter.
 8. Themethod of claim 1, further comprising passing the filtrate onto ananalyser structure containing discrete regions, to which the surfacemarkers are bound.
 9. The method of claim 8, further comprisingincubating the filtrate in the analyser structure.
 10. The method ofclaim 1, wherein the at least one surface marker of the cells includesone or more pathogen surface markers that facilitate identifyingpathogens in the biological sample.
 11. The method of claim 1, whereinthe at least one surface marker of the cells includes one or moremycoplasma surface markers that facilitate detecting mycoplasma growthin cell lines.
 12. The method of claim 1, wherein the first countparameter of the marker-specific molecules is predetermined.
 13. Themethod of claim 1, further comprising determining, by the sensor or theanalyser, the first count parameter of the marker-specific moleculesprior to generating the filtrate.
 14. The method of claim 1, furthercomprising determining, by the computing device or the analyser, adisease of an individual based on the difference between the first countparameter and the second count parameter.
 15. The method of claim 1,further comprising: maintaining, by the computing device or theanalyser, a plurality of treatment recommendations; and providing, bythe computing device or the analyser, one of the treatmentrecommendations based on determination of the disease of the individual.16. A method for differentiating cells in a biological sample, themethod comprising: contacting the biological sample with marker-specificmolecules against at least one surface marker of the cells, wherein themarker-specific molecules are associated with a count parameter;allowing the cells in the biological sample to bind to themarker-specific molecules to produce bound marker-specific molecules;treating or filtering the biological sample to remove the cells and thebound marker-specific molecules from the biological sample and generatea filtrate; determining, by a sensor or an analyser, a count parameterof the bound marker-specific molecules; and calculating, by theanalyser, a number of the cells of one or more types based on the countparameter of the marker-specific molecules and the count parameter ofthe bound marker-specific molecules.
 17. A system for differentiatingcells in a biological sample, the system comprising: a sampling moduleconfigured to contact the biological sample with marker-specificmolecules against at least one surface marker of the cells and allow thecells in the biological sample to bind to the marker-specific moleculesto produce bound marker-specific molecules, wherein the marker-specificmolecules are associated with a first count parameter; a filterconfigured to filter the biological sample by removing the cells and thebound marker-specific molecules from the biological sample to generate afiltrate; and an analyser configured to determine a second countparameter of the marker-specific molecules in the filtrate and calculatea number of the cells in the biological sample based on the differencebetween the first count parameter and the second count parameter. 18.The the system of claim 17, wherein the analyser includes a computingdevice having at least one processor and a memory, which storesprocessor-executable instructions that, when executed by the at leastone processor, cause the at least one processor to determine the secondcount parameter of the at least one marker-specific molecule in thefiltrate, and calculate the number of the cells in the biological samplebased on the difference between the first count parameter and the secondcount parameter.
 19. The system of claim 17, wherein the analyserincludes a computing device having at least one processor and a memory,which stores processor-executable instructions that, when executed bythe at least one processor, cause the at least one processor todetermine the second concentration of the at least one marker-specificmolecule in the filtrate, and calculate the number of the cells in thebiological sample based on the difference between the firstconcentration and the second concentration.
 20. A system fordifferentiating cells in a biological sample, the system comprising: asampling module configured to contact the biological sample withmarker-specific molecules against at least one surface marker of thecells and allow the cells in the biological sample to bind to themarker-specific molecules to produce bound marker-specific molecules,wherein the marker-specific molecules are associated with a first countparameter; a filter configured to filter the biological sample byremoving the cells and the bound marker-specific molecules from thebiological sample; and an analyser configured to determine a secondcount parameter of the marker-specific molecule bound to the cells andcalculate a number of the cells in the biological sample based on thedifference between the first count parameter and the second countparameter. 21-63. (canceled)